Mechanical power output is a key performance-determining variable in many cyclic sports. In rowing, instantaneous power output is commonly determined as the dot product of handle force moment and oar angular velocity. The aim of this study was to show that this commonly used proxy is theoretically flawed and to provide an indication of the magnitude of the error. To obtain a consistent dataset, simulations were performed using a previously proposed forward dynamical model. Inputs were previously recorded rower kinematics and horizontal oar angle, at 20 and 32 strokes∙min−1. From simulation outputs, true power output and power output according to the common proxy were calculated. The error when using the common proxy was quantified as the difference between the average power output according to the proxy and the true average power output (P̅residual), and as the ratio of this difference to the true average power output (ratiores./rower). At stroke rate 20, P̅residual was 27.4 W and ratiores./rower was 0.143; at stroke rate 32, P̅residual was 44.3 W and ratiores./rower was 0.142. Power output in rowing appears to be underestimated when calculated according to the common proxy. Simulations suggest this error to be at least 10% of the true power output.
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From the article: "Project execution in the construction industry faces major challenges, e.g. difficulty in coordination and cooperation. Operational procurement during project execution is no exception. In this paper we construct a maturity model, based on earlier work, consisting of six dimensions (goal, control, process, organization, information, technology) and five maturity stages (transactional-oriented, commercial-oriented, coordination, internal-optimized, external-optimized). The model can be used to determine the level of procurement maturity for each of the dimensions, and for the determination of a strategy for growth in the construction industry. With input from a major construction firm in the Netherlands, through simulating tooling, the model is evaluated for its contribution to growth in operational excellence. Results of the simulation show support for a relation between maturity growth and increased operational excellence." Recommended Citation Xing, Xiaochun; Versendaal, Johan; van den Akker, Marjan; and De Bevere, Bastiaan, "Maturity of Operational Procurement in the Construction Industry: A Business/IT-Alignment Perspective" (2011). BLED 2011 Proceedings. Paper 22. http://aisel.aisnet.org/bled2011/22 Affiliation: Xing Xiaochun - Swets Information Services, Netherlands; Johan Versendaal - Utrecht University, Netherlands; HU University of Applied Sciences, Netherlands; Marjan van den Akker - Utrecht University, Netherlands; Bastiaan De Bevere - Ballast Nedam, Netherlands.
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The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
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Introduction: Given the complexity of teaching clinical reasoning to (future) healthcare professionals, the utilization of serious games has become popular for supporting clinical reasoning education. This scoping review outlines games designed to support teaching clinical reasoning in health professions education, with a specific emphasis on their alignment with the 8-step clinical reasoning cycle and the reflective practice framework, fundamental for effective learning. Methods: A scoping review using systematic searches across seven databases (PubMed, CINAHL, ERIC, PsycINFO, Scopus, Web of Science, and Embase) was conducted. Game characteristics, technical requirements, and incorporation of clinical reasoning cycle steps were analyzed. Additional game information was obtained from the authors. Results: Nineteen unique games emerged, primarily simulation and escape room genres. Most games incorporated the following clinical reasoning steps: patient consideration (step 1), cue collection (step 2), intervention (step 6), and outcome evaluation (step 7). Processing information (step 3) and understanding the patient’s problem (step 4) were less prevalent, while goal setting (step 5) and reflection (step 8) were least integrated. Conclusion: All serious games reviewed show potential for improving clinical reasoning skills, but thoughtful alignment with learning objectives and contextual factors is vital. While this study aids health professions educators in understanding how games may support teaching of clinical reasoning, further research is needed to optimize their effective use in education. Notably, most games lack explicit incorporation of all clinical reasoning cycle steps, especially reflection, limiting its role in reflective practice. Hence, we recommend prioritizing a systematic clinical reasoning model with explicit reflective steps when using serious games for teaching clinical reasoning.
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Background Wheelchair tennis, a globally popular sport, features a professional tour spanning 40 countries and over 160 tournaments. Despite its widespread appeal, information about the physical demands of wheelchair tennis is scattered across various studies, necessitating a comprehensive systematic review to synthesise available data. Objective The aim was to provide a detailed synthesis of the physical demands associated with wheelchair tennis, encompassing diverse factors such as court surfaces, performance levels, sport classes, and sexes. Methods We conducted comprehensive searches in the PubMed, Embase, CINAHL, and SPORTDiscus databases, covering articles from inception to March 1, 2023. Forward and backward citation tracking from the included articles was carried out using Scopus, and we established eligibility criteria following the Population, Exposure, Comparison, Outcome, and Study design (PECOS) framework. Our study focused on wheelchair tennis players participating at regional, national, or international levels, including both juniors and adults, and open and quad players. We analysed singles and doubles matches and considered sex (male, female), sport class (open, quad), and court surface type (hard, clay, grass) as key comparative points. The outcomes of interest encompassed play duration, on-court movement, stroke performance, and physiological match variables. The selected study designs included observational cross-sectional, longitudinal, and intervention studies (baseline data only). We calculated pooled means or mean differences with 95% confidence intervals (CIs) and employed a random-effects meta-analysis with robust variance estimation. We assessed heterogeneity using Cochrane Q and 95% prediction intervals. Results Our literature search retrieved 643 records, with 24 articles meeting our inclusion criteria. Most available information focused on international male wheelchair tennis players in the open division, primarily competing in singles on hard courts. Key findings (mean [95% CI]) for these players on hard courts were match duration 65.9 min [55.0–78.8], set duration 35.0 min [28.2–43.5], game duration 4.6 min [0.92–23.3], rally duration 6.1 s [3.7–10.2], effective playing time 19.8% [18.9–20.7], and work-to-rest ratio 1:4.1 [1:3.7–1:4.4]. Insufficient data were available to analyse play duration for female players. However, for the available data on hard court matches, the average set duration was 34.8 min [32.5–37.2]. International male players on hard court covered an average distance per match of 3859 m [1917–7768], with mean and peak average forward speeds of 1.06 m/s [0.85–1.32] and 3.55 m/s [2.92–4.31], respectively. These players executed an average of 365.9 [317.2–422.1] strokes per match, 200.6 [134.7–299.0] per set, 25.4 [16.7–38.7] per game, and 3.4 [2.6–4.6] per rally. Insufficient data were available for a meta-analysis of female players’ on-court movement and stroke performance. The average and peak heart rates of international male players on hard court were 134.3 [124.2–145.1] and 166.0 [132.7–207.6] beats per minute, and the average match heart rate expressed as a percentage of peak heart rate was 74.7% [46.4–100]. We found no studies concerning regional players or juniors, and only one study on doubles match play. Conclusions While we present a comprehensive overview of the physical demands of wheelchair tennis, our understanding predominantly centres around international male players competing on hard courts in the open division. To attain a more comprehensive insight into the sport’s physical requirements, future research should prioritise the inclusion of data on female and quad players, juniors, doubles, and matches played on clay and grass court surfaces. Such endeavours will facilitate the development of more tailored and effective training programmes for wheelchair tennis players and coaches.
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Our approach builds on both the design traditions of participatory design and embodiment. We attempt to connect these traditions to the existing body of knowledge on persuasion. First we describe some basic theoretical concepts and infer how they influence persuasive design. Then we present a basic framework with which we intend to address the different abstraction layers involved. Finally, we discuss the principal differences and meeting areas between the disciplines of design and communication, ending up with some considerations for a persuasion toolbox that is intended to help communication professionals and designers effectively design behavior change interventions that fit the messy lives of people in the real world
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Artificial Intelligence systems are more and more being introduced into first response; however, this introduction needs to be done responsibly. While generic claims on what this entails already exist, more details are required to understand the exact nature of responsible application of AI within the first response domain. The context in which AI systems are applied largely determines the ethical, legal, and societal impact and how to deal with this impact responsibly. For that reason, we empirically investigate relevant human values that are affected by the introduction of a specific AI-based Decision Aid (AIDA), a decision support system under development for Fire Services in the Netherlands. We held 10 expert group sessions and discussed the impact of AIDA on different stakeholders. This paper presents the design and implementation of the study and, as we are still in process of analyzing the sessions in detail, summarizes preliminary insights and steps forward.
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Conference proceedings International Symposium on Intelligent Manufacturing Environments
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For twenty years, typical outdoor lifestyle sports like rafting, snowboarding and rock climbing, which used to be exclusively practised in natural environments, are being offered in controlled artificial settings. This process can be described as 'the indoorisation of outdoor sports'. With this development, questions of authenticity arise. Are these new, commercial forms still authentic lifestyle sports? And can we consider the participants in these indoorised lifestyle sports as authentic? There has been a discussion about authenticity in lifestyle sports since its worldwide popularisation and it is worth to reconsider this discussion against the background of new, commercial versions of lifestyle sports. Therefore, in this paper a qualitative analysis is offered about the consumption of a constructed authenticity in a cultural context increasingly characterized by artificialization.
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The Dutch greenhouse horticulture industry is characterized by world leadership in high-tech innovation. The dynamics of this playing field are innovation in production systems and automation, reduction in energy consumption and sharing limited space. However, international competitive advantage of the industry is under pressure and sustainable growth of individual enterprises is no longer a certainty. The sector's ambition is to innovate better and grow faster than the competition in the rest of the world. Realizing this ambition requires strengthening the knowledge base, stimulating entrepreneurship, innovation (not just technological, but especially business process innovation). It also requires educating and professionalizing people. However, knowledge transfer in this industry is often fragmented and innovation through horizontal and vertical collaboration throughout the value chain is limited. This paper focuses on the question: how can the grower and the supplier in the greenhouse horticulture chain gain competitive advantage through radical product and process innovation. The challenge lies in time- to-market, in customer relationship, in developing new product/market combinations and in innovative entrepreneurship. In this paper an innovation and entrepreneurial educational and research programme is introduced. The programme aims at strengthening multidisciplinary collaboration between enterprise, education and research. Using best practice examples, the paper illustrates how companies can realize growth and improve the innovative capacity of the organization as well as the individual by linking economic and social sustainability. The paper continues to show how participants of the program develop competencies by means of going through a learning cycle of single-loop, double-loop and triple loop learning: reduction of mistakes, change towards new concepts and improvement of the ability to learn. Finally, the paper illustrates the importance of combining enterprise, education and research in regional networks, with examples from the greenhouse horticulture sector. These networks generate economic growth and international competitiveness by acting as business accelerators.
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